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Research Associate (Doctoral candidate) (f/m) in Information Extraction/ Information Filtering @GESIS

For the department WTS at our location in Cologne, we are looking for a

Research Associate (Doctoral candidate) (f/m) in Information Extraction/ Information Filtering

(salary group TV-L EG 13, 100%, limited to 24 month)

starting on September 1, 2016.

GESIS – Leibniz-Institute for the Social Sciences is the largest infrastructure institution for the Social Sciences in Germany. With more than 300 employees in two locations (Mannheim and Cologne) GESIS render substantial, nationally and internationally relevant research-based infrastructure services.

The GESIS department “Knowledge Technologies for the Social Sciences” (WTS) is focused on advancing and improving digital services for the Social Sciences on the basis of novel knowledge technologies. To ensure a high quality of GESIS services WTS is carrying out research in applied Computer Science, in particular in the fields Web Science, Semantic Web, Linked Open Data and Information Retrieval.


In the DFG-funded project “Extraction of Citations from PDF Documents (EXCITE)” [1] we develop together with our project partner the WeST institute at University Koblenz-Landau (Prof. Steffen Staab) a platform to extract literature references from full texts and further process this data into linked data.

Your tasks will be:

  • Development of data extraction techniques (extraction of literature references/citations) from PDF files,
  • Conception and development of web service APIs for citation extraction,
  • Implementation of information filtering and data linking methods,
  • Integration of the extracted data in productive information systems,
  • Publication of project results as Linked Data and
  • Evaluation of the techniques / process pipeline and publication of the project results.

Your profile:

  • Excellent university degree in computer science or comparable field,
  • Solid experience in software development in Java, Web- and XML-technologies, data-base and search technologies,
  • Very good knowledge and experience in text mining technologies and recent search engine technologies (e.g. SOLR) and with Digital Libraries,
  • Knowledge in Perl Programming Language desired,
  • Knowledge in the development of portal and discovery systems desired,
  • Knowledge in the further development of Natural Language Processing (NLP) techniques desired,
  • High degree of problem solving skills and distinct communication skills and team capabilities and
  • Good knowledge in spoken and written German and English.

GESIS guarantees that guidelines regarding employment laws for the disabled and handicapped as well as laws and regulations governing part-time employment will be observed. GESIS promotes the professional equality for women and men and is certified by the European work & family audit.

For further information concerning job description please contact Dr. Philipp Mayr under telephone +49 (0)221-47694-533 or via Email

We only process online applications. Please apply her until July 04, 2016

The number is WTS-37.